期刊
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
卷 276, 期 1668, 页码 2755-2762出版社
ROYAL SOC
DOI: 10.1098/rspb.2009.0405
关键词
self-organization; crowds; pedestrian interactions; social force model; controlled experiments
资金
- CNRS (Concerted Action: 'Complex Systems in Human and Social Sciences')
- University Paul Sabatier (Aides Ponctuelles de Cooperation)
- ETH Zurrich
- CNRS
- French Ministry of Education, Research and Technology
In animal societies as well as in human crowds, many observed collective behaviours result from self-organized processes based on local interactions among individuals. However, models of crowd dynamics are still lacking a systematic individual-level experimental verification, and the local mechanisms underlying the formation of collective patterns are not yet known in detail. We have conducted a set of well-controlled experiments with pedestrians performing simple avoidance tasks in order to determine the laws ruling their behaviour during interactions. The analysis of the large trajectory dataset was used to compute a behavioural map that describes the average change of the direction and speed of a pedestrian for various interaction distances and angles. The experimental results reveal features of the decision process when pedestrians choose the side on which they evade, and show a side preference that is amplified by mutual interactions. The predictions of a binary interaction model based on the above findings were then compared with bidirectional flows of people recorded in a crowded street. Simulations generate two asymmetric lanes with opposite directions of motion, in quantitative agreement with our empirical observations. The knowledge of pedestrian behavioural laws is an important step ahead in the understanding of the underlying dynamics of crowd behaviour and allows for reliable predictions of collective pedestrian movements under natural conditions.
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